This invention relates to the field of data signal processing, and more particularly to a method and apparatus for discriminating noise from linear target tracks in three-dimensional threshold mosaic sensor data.
The typical processing sequence associated with the detection and tracking of moving targets using a staring mosaic sensor system can be broken down into five functional subprocessors: Background Elimination, Event Detection, Track Detection, Track Association and Trajectory Estimation. After the low frequency portion of the background has been eliminated, the simplest type of event detection usually considered is single bit thresholding of the residual data frames. The resulting binary data frames are then inputted to the track detection processor that discriminates target bits from false point bits by using the linear nature of the target tracks in the space-time data.
The track search procedure can be very costly in terms of its computational speed and memory requirements, especially in the case of high false point rates on the incoming data. This in turn results in requiring either the setting of a high threshold in the Event Detection processor which will cause dim targets to go undetected, or that the signal to noise ratio on those dim targets be sufficiently high so as to allow for high thresholds with acceptance probability of target detection. Since the requirement of high signal-to-noise ratio greatly impacts the size and performance required of the optical systems, there are significant gains to be realized by developing track detection techniques which can function with high false point rates on the thresholded data.
Filtering techniques for discriminating noise from signal are well known in the art. The ideal filter, commonly referred to as a matched filter, is one where the output signal-to-noise ratio is maximized.
Many attempts have been made to approximate the characteristics of the ideal filter utilizing analog signal processing techniques, however, the rigid control of device parameters necessitated by the utilization of analog devices and the susceptibility of analog devices to noise have certain limitations in some applications.
Similarly, attempts have been made to approximate the characteristics of the ideal filter utilizing digital signal processing techniques, however, they often require precision components, such as, analog-to-digital converters, high-speed multipliers and adders. These components increase the cost of the filter considerably and in some applications may present a cost justification limitation.
It is accordingly a general object of the present invention to overcome the aforementioned limitations and drawbacks associated with conventional filtering techniques and to fulfill the needs mentioned above.
It is a particular object of the invention to provide an improved method and apparatus for discriminating noise from signal.
It is a further object of the invention to provide a Boolean filtering method and apparatus for discriminating noise from linear target tracks in three-dimensional mosaic sensor data.
Other objects will be apparent in the following detailed description and the practice of the invention.